{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from pathlib import Path\n",
    "import os\n",
    "import sys\n",
    "import tarfile\n",
    "import tensorflow as tf\n",
    "from IPython.display import display, Image\n",
    "from scipy import ndimage\n",
    "import h5py\n",
    "from PIL import Image\n",
    "import PIL.Image as Image\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DigitStructFile:\n",
    "    def __init__(self, inf):\n",
    "        self.inf = h5py.File(inf, 'r')\n",
    "        self.digitStructName = self.inf['digitStruct']['name']\n",
    "        self.digitStructBbox = self.inf['digitStruct']['bbox']\n",
    "\n",
    "    def getName(self, n):\n",
    "        return ''.join([chr(c[0]) for c in self.inf[self.digitStructName[n][0]].value])\n",
    "\n",
    "    def bboxHelper(self, attr):\n",
    "        if (len(attr) > 1):\n",
    "            attr = [self.inf[attr.value[j].item()].value[0][0]\n",
    "                    for j in range(len(attr))]\n",
    "        else:\n",
    "            attr = [attr.value[0][0]]\n",
    "        return attr\n",
    "\n",
    "    def getBbox(self, n):\n",
    "        bbox = {}\n",
    "        bb = self.digitStructBbox[n].item()\n",
    "        bbox['height'] = self.bboxHelper(self.inf[bb][\"height\"])\n",
    "        bbox['label'] = self.bboxHelper(self.inf[bb][\"label\"])\n",
    "        bbox['left'] = self.bboxHelper(self.inf[bb][\"left\"])\n",
    "        bbox['top'] = self.bboxHelper(self.inf[bb][\"top\"])\n",
    "        bbox['width'] = self.bboxHelper(self.inf[bb][\"width\"])\n",
    "        return bbox\n",
    "\n",
    "    def getDigitStructure(self, n):\n",
    "        s = self.getBbox(n)\n",
    "        s['name'] = self.getName(n)\n",
    "        return s\n",
    "\n",
    "    def getAllDigitStructure(self):\n",
    "        return [self.getDigitStructure(i) for i in range(len(self.digitStructName))]\n",
    "\n",
    "    def getAllDigitStructure_ByDigit(self):\n",
    "        pictDat = self.getAllDigitStructure()\n",
    "        result = []\n",
    "        structCnt = 1\n",
    "        for i in range(len(pictDat)):\n",
    "            item = {'filename': pictDat[i][\"name\"]}\n",
    "            figures = []\n",
    "            for j in range(len(pictDat[i]['height'])):\n",
    "                figure = {}\n",
    "                figure['height'] = pictDat[i]['height'][j]\n",
    "                figure['label'] = pictDat[i]['label'][j]\n",
    "                figure['left'] = pictDat[i]['left'][j]\n",
    "                figure['top'] = pictDat[i]['top'][j]\n",
    "                figure['width'] = pictDat[i]['width'][j]\n",
    "                figures.append(figure)\n",
    "            structCnt = structCnt + 1\n",
    "            item['boxes'] = figures\n",
    "            result.append(item)\n",
    "        return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_dataset(data, folder):\n",
    "\n",
    "    dataset = np.ndarray([len(data), 32, 32, 1], dtype='float32')\n",
    "    labels = np.ones([len(data), 6], dtype=int) * 10\n",
    "    for i in np.arange(len(data)):\n",
    "        filename = data[i]['filename']\n",
    "        fullname = os.path.join(folder, filename)\n",
    "        im = Image.open(fullname)\n",
    "        boxes = data[i]['boxes']\n",
    "        num_digit = len(boxes)\n",
    "        labels[i, 0] = num_digit\n",
    "        top = np.ndarray([num_digit], dtype='float32')\n",
    "        left = np.ndarray([num_digit], dtype='float32')\n",
    "        height = np.ndarray([num_digit], dtype='float32')\n",
    "        width = np.ndarray([num_digit], dtype='float32')\n",
    "        for j in np.arange(num_digit):\n",
    "            if j < 5:\n",
    "                labels[i, j+1] = boxes[j]['label']\n",
    "                if boxes[j]['label'] == 10:\n",
    "                    labels[i, j+1] = 0\n",
    "            else:\n",
    "                print('#', i, 'image has more than 5 digits.')\n",
    "            top[j] = boxes[j]['top']\n",
    "            left[j] = boxes[j]['left']\n",
    "            height[j] = boxes[j]['height']\n",
    "            width[j] = boxes[j]['width']\n",
    "\n",
    "        im_top = np.amin(top)\n",
    "        im_left = np.amin(left)\n",
    "        im_height = np.amax(top) + height[np.argmax(top)] - im_top\n",
    "        im_width = np.amax(left) + width[np.argmax(left)] - im_left\n",
    "\n",
    "        im_top = np.floor(im_top - 0.1 * im_height)\n",
    "        im_left = np.floor(im_left - 0.1 * im_width)\n",
    "        im_bottom = np.amin([np.ceil(im_top + 1.2 * im_height), im.size[1]])\n",
    "        im_right = np.amin([np.ceil(im_left + 1.2 * im_width), im.size[0]])\n",
    "\n",
    "        im = im.crop((im_left, im_top, im_right, im_bottom)\n",
    "                     ).resize([32, 32], Image.ANTIALIAS)\n",
    "        im = np.dot(np.array(im, dtype='float32'),\n",
    "                    [[0.2989], [0.5870], [0.1140]])\n",
    "        mean = np.mean(im, dtype='float32')\n",
    "        std = np.std(im, dtype='float32', ddof=1)\n",
    "        if std < 1e-4:\n",
    "            std = 1.\n",
    "        im = (im - mean) / std\n",
    "        dataset[i, :, :, :] = im[:, :, :]\n",
    "    return dataset, labels        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for folder in ['train', 'test', 'extra']:\n",
    "    print(folder)\n",
    "    path = Path('images', 'svhn', folder)\n",
    "    target = path  / 'digitStruct.mat'\n",
    "    dsf = DigitStructFile(target)\n",
    "    data = dsf.getAllDigitStructure_ByDigit()\n",
    "    dataset, labels = generate_dataset(data, path)\n",
    "    dataset = dataset.reshape(dataset.shape[0], -1)\n",
    "    with pd.HDFStore('images/svnh/data.h5') as store:\n",
    "        store.put(f'{folder}/data', pd.DataFrame(dataset))\n",
    "        store.put(f'{folder}/labels', pd.DataFrame(labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore('images/svhn/data.h5') as store:\n",
    "    X_train = store['train/data'].values.reshape(-1, 32, 32, 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 16 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(nrows=2, ncols=8, figsize=(20, 5))\n",
    "axes = axes.flatten()\n",
    "for i, ax in enumerate(axes):\n",
    "    ax.imshow(np.squeeze(X_train[i]))\n",
    "    ax.axis('off')\n",
    "fig.savefig('images/svhn', dpi=300);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {},
   "toc_section_display": true,
   "toc_window_display": false
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
